RRepoGEO

REPOGEO REPORT · LITE

strongdm/attractor

Default branch main · commit fb57a55e · scanned 5/8/2026, 2:22:50 PM

GitHub: 1,150 stars · 182 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface strongdm/attractor, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Refine the About description for clarity on purpose

    Why:

    CURRENT
    nlspec of StrongDM's Attractor, a non-interactive Coding Agent sufficient for use in a Software Factory
    COPY-PASTE FIX
    NLSpecs for StrongDM's Attractor: a non-interactive Coding Agent designed for building your own AI-powered Software Factory.
  • mediumreadme#2
    Add a concise tagline to the README H1

    Why:

    CURRENT
    # Attractor
    COPY-PASTE FIX
    # Attractor: NLSpecs for your AI Software Factory's Coding Agent

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface strongdm/attractor
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GitHub Actions
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GitHub Actions · recommended 1×
  2. GitLab CI/CD · recommended 1×
  3. argoproj/argo-workflows · recommended 1×
  4. apache/airflow · recommended 1×
  5. OpenAI GPT-4 · recommended 1×
  • CATEGORY QUERY
    How to build an automated software factory using non-interactive coding agents?
    you: not recommended
    AI recommended (in order):
    1. GitHub Actions
    2. GitLab CI/CD
    3. Argo Workflows (argoproj/argo-workflows)
    4. Apache Airflow (apache/airflow)
    5. OpenAI GPT-4
    6. GPT-3.5 Turbo
    7. Anthropic Claude 3
    8. Google Gemini
    9. Llama 3
    10. Code Llama
    11. Git (git/git)
    12. GitHub
    13. GitLab
    14. Bitbucket
    15. LangChain (langchain-ai/langchain)
    16. LlamaIndex (run-llama/llama_index)
    17. Pinecone
    18. Weaviate (weaviate/weaviate)
    19. Chroma (chroma-core/chroma)
    20. SonarQube (SonarSource/sonarqube)
    21. ESLint (eslint/eslint)
    22. Pylint (pylint-dev/pylint)
    23. Jest (jestjs/jest)
    24. Pytest (pytest-dev/pytest)
    25. JUnit (junit-team/junit5)
    26. Terraform (hashicorp/terraform)
    27. Kubernetes (kubernetes/kubernetes)
    28. Docker (moby/moby)

    AI recommended 28 alternatives but never named strongdm/attractor. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Frameworks for creating custom AI coding agents from natural language specifications?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. AutoGPT
    4. BabyAGI
    5. CrewAI
    6. OpenAI Assistants API
    7. Haystack
    8. Guidance

    AI recommended 8 alternatives but never named strongdm/attractor. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of strongdm/attractor?
    pass
    AI named strongdm/attractor explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts strongdm/attractor in production, what risks or prerequisites should they evaluate first?
    pass
    AI named strongdm/attractor explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo strongdm/attractor solve, and who is the primary audience?
    pass
    AI named strongdm/attractor explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite